Cell Type-Specific Proteins that Promote Resilience to Cognitive Aging and Alzheimer's Disease

促进认知衰老和阿尔茨海默病恢复能力的细胞类型特异性蛋白质

• 批准号: 10846926
• 负责人: CATHERINE COOK KACZOROWSKI
• 金额: $ 155.84万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10846926
• 关键词: Age; Aging; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer' s disease model; Alzheimer' s disease patient; Amino Acids; Amyloid; Attention; Autopsy; Behavior; Cells; Chronology; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Cognitive; Cognitive aging; Cognitive deficits; Communities; Complex; DNA; Data; Data Set; Databases; Disease; Disease Progression; Electrophysiology (science); Environmental Risk Factor; Exhibits; Gene Expression; Gene Expression Profile; Genes; Genetic; Genetic Engineering; Genetic Risk; Genetic Transcription; Genetic Variation; Genomics; Grant; Hand; Hippocampus; Human; Human Genetics; Human Genome; Immune; Impaired cognition; Individual; Ion Channel; Knowledge; Knowledge Portal; Label; Late Onset Alzheimer Disease; Learning; Link; Mediating; Memory; Memory impairment; Meta-Analysis; Metadata; Methods; Microglia; Molecular; Molecular Analysis; Molecular Target; Mouse Strains; Mus; Mutation; Neurobehavioral Manifestations; Neurons; Pathology; Pathway interactions; Patients; Phenotype; Population; Predisposition; Protein Biosynthesis; Proteins; Proteome; Proteomics; RNA; Research; Resources; Sampling; Shiga-Like Toxin I; Synapses; Synaptic plasticity; System; Technology; Testing; The Jackson Laboratory; Time; Transcript; Translating; Variant; Work; aging brain; asymptomatic Alzheimer' s disease; behavioral phenotyping; brain cell; brain tissue; candidate identification; cell type; cognitive function; cohort; data integration; drug discovery; familial Alzheimer disease; genetic approach; high dimensionality; high risk; human data; human model; human tissue; improved; knowledge base; mouse model; multidimensional data; neuroinflammation; neuronal excitability; neuropathology; novel; prevent; promote resilience; protective factors; protein expression; protein protein interaction; resilience; resilience factor; response; segregation; spatial memory; synaptic function; tau Proteins; therapeutic target; transcriptomics; usability

Resilience to brain aging and Alzheimer’s disease (AD) is a phenomenon whereby cognitive functioning is better than predicted based on chronological age, genetic risk and/or advanced neuropathology, likely because of the presence of as yet unidentified protective factors. These factors, once identified, are expected to provide key targets for treatment and prevention of AD. However, significant barriers limit discovery of the genetic mechanisms of resilience using human genetic methods alone, including: difficulties in identifying large numbers of individuals with asymptomatic AD, extracting age and interacting genetic effects from complex human genomes, controlling environmental factors, and obtaining brain tissue from asymptomatic AD cases. Moreover, it is well known that transcript abundance is not sufficient to infer protein abundance, as they differ spatially, temporally, and in response to learning tasks. Yet, our ability to discern how proteomes change across aging and AD progression is limited by the impossibility of longitudinal molecular analyses on human brain tissues, as well as the technology needed to profile cell type-specific proteomes associated with susceptibility versus resilience to AD. To fill these significant technological and knowledge gaps, here we will develop a robust pipeline using the most translationally relevant mouse models of human brain aging and AD (i.e., the AD-BXDs and their non-transgenic Ntg-BXDs controls) to obtain a longitudinal knowledge base of proteomes in specific cell types that we have found to exhibit robust changes in gene expression associated with highly susceptible and highly resilient phenotypes. We will focus on the hippocampus as it is required for spatial memory formation and recall in mice and humans, and hippocampus-dependent memory deficits are common in AD. Indeed, our work and preliminary data suggest that mouse strain differences in the age at onset and progression of cognitive deficits in the AD-BXDs (from extremely susceptible to resilient) result from cell type-specific differences in gene expression in the hippocampus. We will integrate these mouse data with clinical and omics data from NIA-sponsored AMP-AD and Resilience-AD Consortia to identify molecular drivers of cognitive resilience. In Aim 1, we will identify cell type-specific changes in neuron and microglia protein expression associated with resilience to AD using bioorthogonal non-canonical amino acid tagging (BONCAT) in AD-BXDs. In Aim 2, we will translate drivers and molecular networks underlying cognitive resilience to human AD cohorts. In Aim 3, we will leverage the unmatched genetic engineering resources at The Jackson Laboratory to functionally validate ‘in-hand’ resilience candidates by determining their effects on memory, hippocampal neuronal excitability, and synaptic plasticity in CRISPRed AD-BXDs. Using this pipeline, we will thereby discover novel and translationally relevant proteins and complexes for consideration under AMP-AD/TREAT-AD drug discovery pipelines to delay or prevent cognitive symptoms in susceptible AD mice, and ultimately AD patients.

对大脑衰老和阿尔茨海默氏病（AD）的韧性是一种现象，从而基于年龄，遗传风险和/或晚期神经病理学的认知功能优于预测，这可能是因为存在尚未确定的受保护因素。一旦确定，这些因素有望为治疗和预防AD提供关键目标。然而，仅使用人类遗传学方法，限制了重大障碍，限制了发现复原力的遗传机制，包括：难以识别大量患有不对称AD的个体，从复杂的人类基因组中提取年龄和相互作用的遗传效应，控制环境因素以及从不对称AD病例中获得脑组织。此外，众所周知，转录本丰度不足以推断蛋白质丰度，因为它们对学习任务的不同，暂时的不同，暂时的不同。然而，我们辨别蛋白质如何在衰老和AD进展中发生变化的能力受到对人脑组织进行纵向分子分析的可能性的限制，以及对与易感性相关的细胞类型特异性蛋白质与AD的弹性相关的技术所需的技术。为了填补这些重要的技术和知识差距，在这里，我们将使用人脑衰老和AD的最翻译相关的鼠标模型（即AD-BXD及其非Transgenic NTG-BXDS对照组）开发出强大的管道，以获得我们已经在高度抗基因表达的特定细胞中获得蛋白质的纵向知识基础，从而获得了蛋白质的纵向知识基础。我们将专注于海马，因为这是小鼠和人类空间记忆形成和回忆所必需的，并且海马依赖性记忆定义在AD中很常见。实际上，我们的工作和初步数据表明，AD-BXDS中发病年龄的小鼠菌株差异（来自极易感性到弹性）是由于海马中基因表达的细胞类型特异性差异而导致的。我们将将这些小鼠数据与来自NIA赞助的AMP-AD和弹性的临床和OMIC数据集成在一起，以鉴定认知弹性的分子驱动因素。在AIM 1中，我们将在AD-BXDS中使用生物正交的非经氨基氨基酸标记（Boncat）来确定与AD相关的神经元和小胶质细胞蛋白表达的细胞类型特异性变化。在AIM 2中，我们将转换驱动因素和分子网络对人类AD队列的认知弹性。在AIM 3中，我们将利用Jackson实验室的无与伦比的基因工程资源来通过确定记忆的影响，海马神经元的刺激性以及在CRIS PREAD AD-BXDS中的突触可塑性来在功能上验证候选候选者。使用此管道，我们将在AMP-AD/AD-AD药物发现管道下发现新颖和翻译相关的蛋白质和复合物，以延迟或预防易感AD小鼠的认知症状，并最终导致AD患者。